refactor FastApi API코드 리펙토링

apps/pre-processing-service/app/api/endpoints/blog.py

@@ -0,0 +1,21 @@
+# app/api/endpoints/keywords.py
+from fastapi import APIRouter
+from app.decorators.logging import log_api_call
+from ...errors.CustomException import *
+from fastapi import APIRouter
+
+from ...model.schemas import *
+# 이 파일만의 독립적인 라우터를 생성합니다.
+router = APIRouter()
+
+@router.get("/")
+async def root():
+    return {"message": "blog API"}
+
+@router.post("/rag/create", response_model=ResponsetBlogCreate)
+async def rag_create(request: RequestBlogCreate):
+    return {"message": "blog API"}
+
+@router.post("/publish", response_model=RequestBlogPublish)
+async def publish(request: ResponsetBlogPublish):
+    return {"message": "blog API"}

apps/pre-processing-service/app/api/endpoints/keywords.py

@@ -0,0 +1,65 @@
+# app/api/endpoints/keywords.py
+from ...service.keyword_service import keyword_search
+
+from fastapi import APIRouter
+from app.decorators.logging import log_api_call
+from ...errors.CustomException import *
+from fastapi import APIRouter
+from ...errors.CustomException import  *
+from ...model.schemas import RequestNaverSearch, ResponseNaverSearch, RequestSadaguValidate, ResponsetSadaguValidate
+
+# 이 파일만의 독립적인 라우터를 생성합니다.
+router = APIRouter()
+
+@router.get("/")
+async def root():
+    return {"message": "Items API"}
+
+@router.post("/search")
+async def search(request: RequestNaverSearch):
+    """
+    이 엔드포인트는 아래와 같은 JSON 요청을 받습니다.
+    RequestBase와 RequestNaverSearch의 모든 필드를 포함해야 합니다.
+    {
+        "job_id": "job-123",
+        "schedule_id": "schedule-456",
+        "schedule_his_id": 789,
+        "tag": "fastapi",
+        "category": "tech",
+        "start_date": "2025-09-01T12:00:00",
+        "end_date": "2025-09-02T15:00:00"
+    }
+    """
+    job_id = request.job_id
+    schedule_id = request.schedule_id
+    category = request.category
+    keywords = "밥밥밥"
+    return ResponseNaverSearch(
+        job_id=job_id,
+        schedule_id=schedule_id,
+        category=category,
+        keyword=keywords,
+        total_keyword = {1: "바밥밥", 2: "밥밥밥", 3: "바밤바"}
+    )
+
+@router.post("/search/test",response_model=ResponsetSadaguValidate)
+async def search(request: RequestSadaguValidate):
+    """
+    이 엔드포인트는 아래와 같은 JSON 요청을 받습니다.
+    RequestBase와 RequestNaverSearch의 모든 필드를 포함해야 합니다.
+    {
+        "job_id": "job-123",
+        "schedule_id": "schedule-456",
+        "schedule_his_id": 789,
+        "tag": "fastapi",
+        "category": "tech",
+        "start_date": "2025-09-01T12:00:00",
+        "end_date": "2025-09-02T15:00:00"
+    }
+    """
+    response_data= keyword_search(request)
+    return response_data
+
+@router.post("/ssadagu/validate",response_model=ResponseNaverSearch)
+async def ssadagu_validate(request: RequestNaverSearch):
+    return ResponseNaverSearch()

apps/pre-processing-service/app/api/endpoints/embedding.py → apps/pre-processing-service/app/api/endpoints/product.py

@@ -1,12 +1,13 @@
-# app/api/endpoints/embedding.py
 from fastapi import APIRouter
 from app.decorators.logging import log_api_call
 from ...errors.CustomException import *
 from fastapi import APIRouter
 
+from ...model.schemas import *;
+
 # 이 파일만의 독립적인 라우터를 생성합니다.
 router = APIRouter()
 
-@router.get("/")
-async def root():
-    return {"message": "Items API"}
+@router.post("/crawl",response_model=ResponsetSadaguCrawl)
+async def crawl(request: RequestSadaguCrawl):
+    return ResponsetSadaguCrawl()

apps/pre-processing-service/app/api/router.py

@@ -1,15 +1,18 @@
 # app/api/router.py
 from fastapi import APIRouter
-from .endpoints import embedding, processing,test
+from .endpoints import keywords, blog,test,product
 from ..core.config import settings
 
 api_router = APIRouter()
 
 # embedding API URL
-api_router.include_router(embedding.router, prefix="/emb", tags=["Embedding"])
+api_router.include_router(keywords.router, prefix="/keywords", tags=["keyword"])
 
 # processing API URL
-api_router.include_router(processing.router, prefix="/prc", tags=["Processing"])
+api_router.include_router(blog.router, prefix="/blog", tags=["blog"])
+
+#상품 API URL
+api_router.include_router(product.router, prefix="/product", tags=["product"])
 
 #모듈 테스터를 위한 endpoint
 api_router.include_router(test.router, prefix="/test", tags=["Test"])

apps/pre-processing-service/app/errors/handlers.py

@@ -1,65 +1,90 @@
-# app/errors/handlers.py
 from fastapi import Request, status
 from fastapi.responses import JSONResponse
+from pydantic import BaseModel
 from starlette.exceptions import HTTPException as StarletteHTTPException
 from fastapi.exceptions import RequestValidationError
 from .messages import ERROR_MESSAGES, get_error_message
 from ..errors.CustomException import CustomException
 
+class ErrorBaseModel(BaseModel):
+    """
+    모든 에러 응답의 기반이 되는 Pydantic 모델.
+    API의 에러 응답 형식을 통일하는 역할을 합니다.
+    """
+    status_code: int
+    detail: str
+    code: str
+
 # CustomException 핸들러
 async def custom_exception_handler(request: Request, exc: CustomException):
     """
     CustomException을 상속받는 모든 예외를 처리합니다.
     """
+    # 변경점: ErrorBaseModel을 사용하여 응답 본문 생성
+    error_content = ErrorBaseModel(
+        status_code=exc.status_code,
+        detail=exc.detail,
+        code=exc.code
+    )
     return JSONResponse(
         status_code=exc.status_code,
-        content={
-            "error_code": exc.code,
-            "message": exc.detail,
-        },
+        content=error_content.model_dump(),
     )
 
+
 # FastAPI의 HTTPException 핸들러 (예: 404 Not Found)
 async def http_exception_handler(request: Request, exc: StarletteHTTPException):
     """
     FastAPI에서 기본적으로 발생하는 HTTP 관련 예외를 처리합니다.
     """
-    if exc.status_code == status.HTTP_404_NOT_FOUND:
-        # 404 에러의 경우, FastAPI의 기본 "Not Found" 메시지 대신 우리가 정의한 메시지를 사용합니다.
-        message = ERROR_MESSAGES.get(exc.status_code, "요청하신 리소스를 찾을 수 없습니다.")
-    else:
-        # 다른 HTTP 예외들은 FastAPI가 제공하는 detail 메시지를 우선적으로 사용합니다.
-        message = get_error_message(exc.status_code, exc.detail)
+    message = get_error_message(exc.status_code, exc.detail)
 
+    # 변경점: ErrorBaseModel을 사용하여 응답 본문 생성
+    error_content = ErrorBaseModel(
+        status_code=exc.status_code,
+        detail=message,
+        code=f"HTTP_{exc.status_code}"
+    )
     return JSONResponse(
         status_code=exc.status_code,
-        content={
-            "error_code": f"HTTP_{exc.status_code}",
-            "message": message
-        },
+        content=error_content.model_dump(),
     )
 
+
 # Pydantic Validation Error 핸들러 (422)
 async def validation_exception_handler(request: Request, exc: RequestValidationError):
     """
     Pydantic 모델 유효성 검사 실패 시 발생하는 예외를 처리합니다.
     """
+    # 변경점: ErrorBaseModel을 기본 구조로 사용하고, 추가 정보를 더함
+    base_error = ErrorBaseModel(
+        status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
+        detail=ERROR_MESSAGES[status.HTTP_422_UNPROCESSABLE_ENTITY],
+        code="VALIDATION_ERROR"
+    )
+
+    # 모델의 내용과 추가적인 'details' 필드를 결합
+    response_content = base_error.model_dump()
+    response_content["details"] = exc.errors()
+
     return JSONResponse(
         status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
-        content={
-            "error_code": "VALIDATION_ERROR",
-            "message": ERROR_MESSAGES[status.HTTP_422_UNPROCESSABLE_ENTITY],
-            "details": exc.errors(),
-        },
+        content=response_content,
     )
 
+
 # 처리되지 않은 모든 예외 핸들러 (500)
 async def unhandled_exception_handler(request: Request, exc: Exception):
-    # ...
+    """
+    처리되지 않은 모든 예외를 처리합니다.
+    """
+    # 변경점: ErrorBaseModel을 사용하여 응답 본문 생성
+    error_content = ErrorBaseModel(
+        status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+        detail=ERROR_MESSAGES[status.HTTP_500_INTERNAL_SERVER_ERROR],
+        code="INTERNAL_SERVER_ERROR"
+    )
     return JSONResponse(
         status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-        content={
-            "error_code": "INTERNAL_SERVER_ERROR",
-            "message": ERROR_MESSAGES[status.HTTP_500_INTERNAL_SERVER_ERROR],
-        },
+        content=error_content.model_dump(),
     )

apps/pre-processing-service/app/model/schemas.py

@@ -0,0 +1,64 @@
+from datetime import datetime
+from typing import Optional
+from pydantic import BaseModel
+
+
+
+#기본 요청
+class RequestBase(BaseModel):
+    job_id: str
+    schedule_id: str
+    schedule_his_id: Optional[int] = None
+
+#기본 응답
+class ResponseBase(BaseModel):
+    job_id: str
+    schedule_id: str
+    status: str
+
+
+#네이버 키워드 추출
+class RequestNaverSearch(RequestBase):
+    tag: str
+    category: str
+    startDate :datetime
+    endDate :datetime
+
+class ResponseNaverSearch(ResponseBase):
+    category: str
+    keyword: str
+    total_keyword: dict[int, str]
+
+
+#키워드 사다구몰 검증
+class RequestSadaguValidate(RequestBase):
+    tag: str
+    category: str
+
+class ResponsetSadaguValidate(ResponseBase):
+    keyword: str
+
+
+#사다구몰 상품 크롤링
+class RequestSadaguCrawl(RequestBase):
+    tag: str
+    category: str
+
+class ResponsetSadaguCrawl(ResponseBase):
+    pass
+
+#블로그 생성
+class RequestBlogCreate(RequestBase):
+    tag: str
+    category: str
+
+class ResponsetBlogCreate(ResponseBase):
+    pass
+
+#블로그 배포
+class RequestBlogPublish(RequestBase):
+    tag: str
+    category: str
+
+class ResponsetBlogPublish(ResponseBase):
+    pass

apps/pre-processing-service/app/service/keyword_service.py

@@ -0,0 +1,16 @@
+# Pydantic 모델을 가져오기 위해 schemas 파일 import
+from ..model.schemas import RequestNaverSearch
+
+def keyword_search(request: RequestNaverSearch) -> dict:
+    """
+    네이버 검색 요청을 처리하는 비즈니스 로직입니다.
+    입력받은 데이터를 기반으로 응답 데이터를 생성하여 딕셔너리로 반환합니다.
+    """
+
+    response_data = request.model_dump()
+
+    response_data["keyword"] = "밥밥밥"
+    total_keyword = {1: "바밥밥", 2: "밥밥밥", 3: "바밤바"}
+    response_data["total_keyword"] = total_keyword
+
+    return response_data